Project Description

Artificial Intelligence (AI)

Many large tech organizations envision Artificial Intelligence as a new wave of economic potential that provides growth potential for large enterprises. AI builds on the capabilities and knowledge of Big Data and it is therefore important to have a solid foundation of this topic.

A history of AI

Artificial Intelligence (popularly referred to as AI) is intelligence displayed by machines, in contrast to the natural intelligence (NI) displayed by human and other animals. The domain of AI was first envisioned by a handful of computer scientists at the Dartmouth conferences in 1956, and has seen an explosive growth, especially since 2015.

Whereas AI can be considered a complete domain of science by itself, it is strongly interwoven with Big Data because the volume and variety of data sources are often massive (in terms of volume) and diverse (in terms of sensors). Additionally, many of the statistical and machine learning algorithms that are used to analyze Big Data sets, are similar to the ones used in Artificial Intelligence.

An evolution of AI

The knowledge domain of Artificial Intelligence has evolved over the years to include Machine Learning algorithms and finally Deep Learning, which is driving today’s AI explosion.

In the course of the evolution of Artificial Intelligence, the underlying algorithms have become more complex and omnipotent. Besides its technical challenges and complexity, Artificial Intelligence also raises many sociological and ethical questions that makes the subject even more complex.

The evolution of AI, Machine Learning and Deep Learning

Figure 1: The evolution of AI, Machine Learning and Deep Learning

An example of AI Application

A popular example of the application of AI is self-driving cars. The final objective of self-driving cars is to mimic the exact same behaviors as ‘natural’ people would make whilst-driving (or preferably even better behavior without any accidents). The input data that have to be processed need to come from different sensors (high variety) and needs to process thousands of signals every single second (high velocity and high volume) as traffic situations change.

Self-driving car

Figure 2: Example of self-driving car

To learn more about Big Data, visit our Big Data Knowledge Base. For more information, contact us at info@bigdataframework.org or drop us a message in the chatbox.